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<a href="#pub-types">Public 类型</a> &#124;
<a href="#pub-methods">Public 成员函数</a> &#124;
<a href="#pro-methods">Protected 成员函数</a> &#124;
<a href="#pro-attribs">Protected 属性</a> &#124;
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<div class="title">pcl::SACSegmentationFromNormals&lt; PointT, PointNT &gt; 模板类 参考</div>  </div>
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<p><b><a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html" title="SACSegmentationFromNormals represents the PCL nodelet segmentation class for Sample Consensus methods...">SACSegmentationFromNormals</a></b> represents the PCL nodelet segmentation class for Sample Consensus methods and models that require the use of surface normals for estimation.  
 <a href="classpcl_1_1_s_a_c_segmentation_from_normals.html#details">更多...</a></p>

<p><code>#include &lt;<a class="el" href="sac__segmentation_8h_source.html">sac_segmentation.h</a>&gt;</code></p>
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类 pcl::SACSegmentationFromNormals&lt; PointT, PointNT &gt; 继承关系图:</div>
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  <img src="classpcl_1_1_s_a_c_segmentation_from_normals.png" usemap="#pcl::SACSegmentationFromNormals_3C_20PointT_2C_20PointNT_20_3E_map" alt=""/>
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<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-types"></a>
Public 类型</h2></td></tr>
<tr class="memitem:afddb12becb6d865a5814780aacc533c6"><td class="memItemLeft" align="right" valign="top"><a id="afddb12becb6d865a5814780aacc533c6"></a>
typedef <a class="el" href="classpcl_1_1_s_a_c_segmentation.html">SACSegmentation</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::<a class="el" href="classpcl_1_1_point_cloud.html">PointCloud</a>&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloud</b></td></tr>
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typedef PointCloud::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudPtr</b></td></tr>
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typedef PointCloud::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudConstPtr</b></td></tr>
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typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; PointNT &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudN</b></td></tr>
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typedef PointCloudN::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudNPtr</b></td></tr>
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typedef PointCloudN::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudNConstPtr</b></td></tr>
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typedef <a class="el" href="classpcl_1_1_sample_consensus.html">SampleConsensus</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>SampleConsensusPtr</b></td></tr>
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typedef <a class="el" href="classpcl_1_1_sample_consensus_model.html">SampleConsensusModel</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>SampleConsensusModelPtr</b></td></tr>
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typedef <a class="el" href="classpcl_1_1_sample_consensus_model_from_normals.html">SampleConsensusModelFromNormals</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a>, PointNT &gt;::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>SampleConsensusModelFromNormalsPtr</b></td></tr>
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<tr class="inherit_header pub_types_classpcl_1_1_s_a_c_segmentation"><td colspan="2" onclick="javascript:toggleInherit('pub_types_classpcl_1_1_s_a_c_segmentation')"><img src="closed.png" alt="-"/>&#160;Public 类型 继承自 <a class="el" href="classpcl_1_1_s_a_c_segmentation.html">pcl::SACSegmentation&lt; PointT &gt;</a></td></tr>
<tr class="memitem:aa09fbf509ac114962b171cfd14a5dc45 inherit pub_types_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="aa09fbf509ac114962b171cfd14a5dc45"></a>
typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloud</b></td></tr>
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typedef PointCloud::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudPtr</b></td></tr>
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typedef PointCloud::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudConstPtr</b></td></tr>
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typedef <a class="el" href="classpcl_1_1search_1_1_search.html">pcl::search::Search</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>SearchPtr</b></td></tr>
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<tr class="memitem:a690cd433d894b90418e00f7d5867cc07 inherit pub_types_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="a690cd433d894b90418e00f7d5867cc07"></a>
typedef <a class="el" href="classpcl_1_1_sample_consensus.html">SampleConsensus</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>SampleConsensusPtr</b></td></tr>
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typedef <a class="el" href="classpcl_1_1_sample_consensus_model.html">SampleConsensusModel</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>SampleConsensusModelPtr</b></td></tr>
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<tr class="inherit_header pub_types_classpcl_1_1_p_c_l_base"><td colspan="2" onclick="javascript:toggleInherit('pub_types_classpcl_1_1_p_c_l_base')"><img src="closed.png" alt="-"/>&#160;Public 类型 继承自 <a class="el" href="classpcl_1_1_p_c_l_base.html">pcl::PCLBase&lt; PointT &gt;</a></td></tr>
<tr class="memitem:ae2f6f6863a73337858b7a7a054eaae4f inherit pub_types_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="ae2f6f6863a73337858b7a7a054eaae4f"></a>
typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloud</b></td></tr>
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typedef PointCloud::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudPtr</b></td></tr>
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typedef PointCloud::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudConstPtr</b></td></tr>
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typedef boost::shared_ptr&lt; <a class="el" href="structpcl_1_1_point_indices.html">PointIndices</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointIndicesPtr</b></td></tr>
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typedef boost::shared_ptr&lt; <a class="el" href="structpcl_1_1_point_indices.html">PointIndices</a> const  &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointIndicesConstPtr</b></td></tr>
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</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public 成员函数</h2></td></tr>
<tr class="memitem:a6c3a8db014d9ebb9388886888e7389db"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a6c3a8db014d9ebb9388886888e7389db">SACSegmentationFromNormals</a> (bool random=false)</td></tr>
<tr class="memdesc:a6c3a8db014d9ebb9388886888e7389db"><td class="mdescLeft">&#160;</td><td class="mdescRight">Empty constructor.  <a href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a6c3a8db014d9ebb9388886888e7389db">更多...</a><br /></td></tr>
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<tr class="memitem:a32a65052303a8ccc167c0182ab261df6"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a32a65052303a8ccc167c0182ab261df6">setInputNormals</a> (const PointCloudNConstPtr &amp;normals)</td></tr>
<tr class="memdesc:a32a65052303a8ccc167c0182ab261df6"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the input dataset that contains the point normals of the XYZ dataset.  <a href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a32a65052303a8ccc167c0182ab261df6">更多...</a><br /></td></tr>
<tr class="separator:a32a65052303a8ccc167c0182ab261df6"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3cef158b2aec9d1232eb5e0528d2ec91"><td class="memItemLeft" align="right" valign="top"><a id="a3cef158b2aec9d1232eb5e0528d2ec91"></a>
PointCloudNConstPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a3cef158b2aec9d1232eb5e0528d2ec91">getInputNormals</a> () const</td></tr>
<tr class="memdesc:a3cef158b2aec9d1232eb5e0528d2ec91"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the normals of the input XYZ point cloud dataset. <br /></td></tr>
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<tr class="memitem:adffe38382fbb0b511764faf9490140ca"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#adffe38382fbb0b511764faf9490140ca">setNormalDistanceWeight</a> (double distance_weight)</td></tr>
<tr class="memdesc:adffe38382fbb0b511764faf9490140ca"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point normals and the plane normal.  <a href="classpcl_1_1_s_a_c_segmentation_from_normals.html#adffe38382fbb0b511764faf9490140ca">更多...</a><br /></td></tr>
<tr class="separator:adffe38382fbb0b511764faf9490140ca"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:adedec2e769f2f8f126d2ce1bf7fd62e4"><td class="memItemLeft" align="right" valign="top"><a id="adedec2e769f2f8f126d2ce1bf7fd62e4"></a>
double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#adedec2e769f2f8f126d2ce1bf7fd62e4">getNormalDistanceWeight</a> () const</td></tr>
<tr class="memdesc:adedec2e769f2f8f126d2ce1bf7fd62e4"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point normals and the plane normal. <br /></td></tr>
<tr class="separator:adedec2e769f2f8f126d2ce1bf7fd62e4"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a902493eecbbfefce45767a98832d02c6"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a902493eecbbfefce45767a98832d02c6">setMinMaxOpeningAngle</a> (const double &amp;min_angle, const double &amp;max_angle)</td></tr>
<tr class="memdesc:a902493eecbbfefce45767a98832d02c6"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the minimum opning angle for a cone model.  <a href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a902493eecbbfefce45767a98832d02c6">更多...</a><br /></td></tr>
<tr class="separator:a902493eecbbfefce45767a98832d02c6"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a5937ab0420b105b8c17918a9c19f4a1d"><td class="memItemLeft" align="right" valign="top"><a id="a5937ab0420b105b8c17918a9c19f4a1d"></a>
void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a5937ab0420b105b8c17918a9c19f4a1d">getMinMaxOpeningAngle</a> (double &amp;min_angle, double &amp;max_angle)</td></tr>
<tr class="memdesc:a5937ab0420b105b8c17918a9c19f4a1d"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the opening angle which we need minumum to validate a cone model. <br /></td></tr>
<tr class="separator:a5937ab0420b105b8c17918a9c19f4a1d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa6e65931b38d3cfa32afc34b60f896c8"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#aa6e65931b38d3cfa32afc34b60f896c8">setDistanceFromOrigin</a> (const double d)</td></tr>
<tr class="memdesc:aa6e65931b38d3cfa32afc34b60f896c8"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the distance we expect a plane model to be from the origin  <a href="classpcl_1_1_s_a_c_segmentation_from_normals.html#aa6e65931b38d3cfa32afc34b60f896c8">更多...</a><br /></td></tr>
<tr class="separator:aa6e65931b38d3cfa32afc34b60f896c8"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab5b41e1d4b62faf0f09fd3e36920c08c"><td class="memItemLeft" align="right" valign="top"><a id="ab5b41e1d4b62faf0f09fd3e36920c08c"></a>
double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#ab5b41e1d4b62faf0f09fd3e36920c08c">getDistanceFromOrigin</a> () const</td></tr>
<tr class="memdesc:ab5b41e1d4b62faf0f09fd3e36920c08c"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the distance of a plane model from the origin. <br /></td></tr>
<tr class="separator:ab5b41e1d4b62faf0f09fd3e36920c08c"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pub_methods_classpcl_1_1_s_a_c_segmentation"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classpcl_1_1_s_a_c_segmentation')"><img src="closed.png" alt="-"/>&#160;Public 成员函数 继承自 <a class="el" href="classpcl_1_1_s_a_c_segmentation.html">pcl::SACSegmentation&lt; PointT &gt;</a></td></tr>
<tr class="memitem:addeabe3a311db251ef7d0a25879f1f4a inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#addeabe3a311db251ef7d0a25879f1f4a">SACSegmentation</a> (bool random=false)</td></tr>
<tr class="memdesc:addeabe3a311db251ef7d0a25879f1f4a inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Empty constructor.  <a href="classpcl_1_1_s_a_c_segmentation.html#addeabe3a311db251ef7d0a25879f1f4a">更多...</a><br /></td></tr>
<tr class="separator:addeabe3a311db251ef7d0a25879f1f4a inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a0a6a501237dea40ae68c62f364e99cdf inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="a0a6a501237dea40ae68c62f364e99cdf"></a>
virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a0a6a501237dea40ae68c62f364e99cdf">~SACSegmentation</a> ()</td></tr>
<tr class="memdesc:a0a6a501237dea40ae68c62f364e99cdf inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Empty destructor. <br /></td></tr>
<tr class="separator:a0a6a501237dea40ae68c62f364e99cdf inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aaf3488729fa23a602cc0ef2e9480c5f5 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#aaf3488729fa23a602cc0ef2e9480c5f5">setModelType</a> (int model)</td></tr>
<tr class="memdesc:aaf3488729fa23a602cc0ef2e9480c5f5 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">The type of model to use (user given parameter).  <a href="classpcl_1_1_s_a_c_segmentation.html#aaf3488729fa23a602cc0ef2e9480c5f5">更多...</a><br /></td></tr>
<tr class="separator:aaf3488729fa23a602cc0ef2e9480c5f5 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa6ca63b1a3068f27ad7c9aeae462dfe2 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="aa6ca63b1a3068f27ad7c9aeae462dfe2"></a>
int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#aa6ca63b1a3068f27ad7c9aeae462dfe2">getModelType</a> () const</td></tr>
<tr class="memdesc:aa6ca63b1a3068f27ad7c9aeae462dfe2 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the type of SAC model used. <br /></td></tr>
<tr class="separator:aa6ca63b1a3068f27ad7c9aeae462dfe2 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a5fde989b5cec51bbec33cb0973186fe2 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="a5fde989b5cec51bbec33cb0973186fe2"></a>
SampleConsensusPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a5fde989b5cec51bbec33cb0973186fe2">getMethod</a> () const</td></tr>
<tr class="memdesc:a5fde989b5cec51bbec33cb0973186fe2 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the SAC method used. <br /></td></tr>
<tr class="separator:a5fde989b5cec51bbec33cb0973186fe2 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac7b9564ceba35754837b4848cf448d78 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="ac7b9564ceba35754837b4848cf448d78"></a>
SampleConsensusModelPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#ac7b9564ceba35754837b4848cf448d78">getModel</a> () const</td></tr>
<tr class="memdesc:ac7b9564ceba35754837b4848cf448d78 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the SAC model used. <br /></td></tr>
<tr class="separator:ac7b9564ceba35754837b4848cf448d78 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a1f01af4b5cc22e916c4facc145bc9297 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a1f01af4b5cc22e916c4facc145bc9297">setMethodType</a> (int method)</td></tr>
<tr class="memdesc:a1f01af4b5cc22e916c4facc145bc9297 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">The type of sample consensus method to use (user given parameter).  <a href="classpcl_1_1_s_a_c_segmentation.html#a1f01af4b5cc22e916c4facc145bc9297">更多...</a><br /></td></tr>
<tr class="separator:a1f01af4b5cc22e916c4facc145bc9297 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a063b9f3f9beebfe252ef206dfa8fb6f5 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="a063b9f3f9beebfe252ef206dfa8fb6f5"></a>
int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a063b9f3f9beebfe252ef206dfa8fb6f5">getMethodType</a> () const</td></tr>
<tr class="memdesc:a063b9f3f9beebfe252ef206dfa8fb6f5 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the type of sample consensus method used. <br /></td></tr>
<tr class="separator:a063b9f3f9beebfe252ef206dfa8fb6f5 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab303bdf338af51e757095fdcdd7dcf5a inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#ab303bdf338af51e757095fdcdd7dcf5a">setDistanceThreshold</a> (double threshold)</td></tr>
<tr class="memdesc:ab303bdf338af51e757095fdcdd7dcf5a inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Distance to the model threshold (user given parameter).  <a href="classpcl_1_1_s_a_c_segmentation.html#ab303bdf338af51e757095fdcdd7dcf5a">更多...</a><br /></td></tr>
<tr class="separator:ab303bdf338af51e757095fdcdd7dcf5a inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a37153f3267f908eb64719749dd9a5428 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="a37153f3267f908eb64719749dd9a5428"></a>
double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a37153f3267f908eb64719749dd9a5428">getDistanceThreshold</a> () const</td></tr>
<tr class="memdesc:a37153f3267f908eb64719749dd9a5428 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the distance to the model threshold. <br /></td></tr>
<tr class="separator:a37153f3267f908eb64719749dd9a5428 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a47c5241af3824ee197e3a9c1b89806c4 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a47c5241af3824ee197e3a9c1b89806c4">setMaxIterations</a> (int max_iterations)</td></tr>
<tr class="memdesc:a47c5241af3824ee197e3a9c1b89806c4 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the maximum number of iterations before giving up.  <a href="classpcl_1_1_s_a_c_segmentation.html#a47c5241af3824ee197e3a9c1b89806c4">更多...</a><br /></td></tr>
<tr class="separator:a47c5241af3824ee197e3a9c1b89806c4 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:adad96aff89dd14bd02ae5790b701e519 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="adad96aff89dd14bd02ae5790b701e519"></a>
int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#adad96aff89dd14bd02ae5790b701e519">getMaxIterations</a> () const</td></tr>
<tr class="memdesc:adad96aff89dd14bd02ae5790b701e519 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get maximum number of iterations before giving up. <br /></td></tr>
<tr class="separator:adad96aff89dd14bd02ae5790b701e519 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a6c436f52078056b626aba0c36b819235 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a6c436f52078056b626aba0c36b819235">setProbability</a> (double probability)</td></tr>
<tr class="memdesc:a6c436f52078056b626aba0c36b819235 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the probability of choosing at least one sample free from outliers.  <a href="classpcl_1_1_s_a_c_segmentation.html#a6c436f52078056b626aba0c36b819235">更多...</a><br /></td></tr>
<tr class="separator:a6c436f52078056b626aba0c36b819235 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a41f0f4101d35fcffd17923204989fbf0 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="a41f0f4101d35fcffd17923204989fbf0"></a>
double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a41f0f4101d35fcffd17923204989fbf0">getProbability</a> () const</td></tr>
<tr class="memdesc:a41f0f4101d35fcffd17923204989fbf0 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the probability of choosing at least one sample free from outliers. <br /></td></tr>
<tr class="separator:a41f0f4101d35fcffd17923204989fbf0 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:acd7cb38442e52a3df81bc0fd28c07646 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#acd7cb38442e52a3df81bc0fd28c07646">setOptimizeCoefficients</a> (bool optimize)</td></tr>
<tr class="memdesc:acd7cb38442e52a3df81bc0fd28c07646 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set to true if a coefficient refinement is required.  <a href="classpcl_1_1_s_a_c_segmentation.html#acd7cb38442e52a3df81bc0fd28c07646">更多...</a><br /></td></tr>
<tr class="separator:acd7cb38442e52a3df81bc0fd28c07646 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a5f2152f5157113171a2d0a077ad17731 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="a5f2152f5157113171a2d0a077ad17731"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a5f2152f5157113171a2d0a077ad17731">getOptimizeCoefficients</a> () const</td></tr>
<tr class="memdesc:a5f2152f5157113171a2d0a077ad17731 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the coefficient refinement internal flag. <br /></td></tr>
<tr class="separator:a5f2152f5157113171a2d0a077ad17731 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a18ba57a99fbbcb0f2d0500b0d21579d2 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a18ba57a99fbbcb0f2d0500b0d21579d2">setRadiusLimits</a> (const double &amp;min_radius, const double &amp;max_radius)</td></tr>
<tr class="memdesc:a18ba57a99fbbcb0f2d0500b0d21579d2 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the minimum and maximum allowable radius limits for the model (applicable to models that estimate a radius)  <a href="classpcl_1_1_s_a_c_segmentation.html#a18ba57a99fbbcb0f2d0500b0d21579d2">更多...</a><br /></td></tr>
<tr class="separator:a18ba57a99fbbcb0f2d0500b0d21579d2 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae02b4d2a62f5dc94deb71f3412b93916 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#ae02b4d2a62f5dc94deb71f3412b93916">getRadiusLimits</a> (double &amp;min_radius, double &amp;max_radius)</td></tr>
<tr class="memdesc:ae02b4d2a62f5dc94deb71f3412b93916 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the minimum and maximum allowable radius limits for the model as set by the user.  <a href="classpcl_1_1_s_a_c_segmentation.html#ae02b4d2a62f5dc94deb71f3412b93916">更多...</a><br /></td></tr>
<tr class="separator:ae02b4d2a62f5dc94deb71f3412b93916 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac8a399afca15a3e2dcbf491a8de3e2f1 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#ac8a399afca15a3e2dcbf491a8de3e2f1">setSamplesMaxDist</a> (const double &amp;radius, SearchPtr search)</td></tr>
<tr class="memdesc:ac8a399afca15a3e2dcbf491a8de3e2f1 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the maximum distance allowed when drawing random samples  <a href="classpcl_1_1_s_a_c_segmentation.html#ac8a399afca15a3e2dcbf491a8de3e2f1">更多...</a><br /></td></tr>
<tr class="separator:ac8a399afca15a3e2dcbf491a8de3e2f1 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a968404675723ac44d5cb8fca689fd620 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a968404675723ac44d5cb8fca689fd620">getSamplesMaxDist</a> (double &amp;radius)</td></tr>
<tr class="memdesc:a968404675723ac44d5cb8fca689fd620 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get maximum distance allowed when drawing random samples  <a href="classpcl_1_1_s_a_c_segmentation.html#a968404675723ac44d5cb8fca689fd620">更多...</a><br /></td></tr>
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<tr class="memitem:a23abc3e522ccb2b2846a6c9b0cf7b7d3 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a23abc3e522ccb2b2846a6c9b0cf7b7d3">setAxis</a> (const Eigen::Vector3f &amp;ax)</td></tr>
<tr class="memdesc:a23abc3e522ccb2b2846a6c9b0cf7b7d3 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the axis along which we need to search for a model perpendicular to.  <a href="classpcl_1_1_s_a_c_segmentation.html#a23abc3e522ccb2b2846a6c9b0cf7b7d3">更多...</a><br /></td></tr>
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<tr class="memitem:af521155221e948e151b726cd76495fd0 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="af521155221e948e151b726cd76495fd0"></a>
Eigen::Vector3f&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#af521155221e948e151b726cd76495fd0">getAxis</a> () const</td></tr>
<tr class="memdesc:af521155221e948e151b726cd76495fd0 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the axis along which we need to search for a model perpendicular to. <br /></td></tr>
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<tr class="memitem:a7a2dc31039a1717f83ca281f6970eb18 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a7a2dc31039a1717f83ca281f6970eb18">setEpsAngle</a> (double ea)</td></tr>
<tr class="memdesc:a7a2dc31039a1717f83ca281f6970eb18 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the angle epsilon (delta) threshold.  <a href="classpcl_1_1_s_a_c_segmentation.html#a7a2dc31039a1717f83ca281f6970eb18">更多...</a><br /></td></tr>
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<tr class="memitem:a93f67b554b55b3f10170065713263910 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="a93f67b554b55b3f10170065713263910"></a>
double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a93f67b554b55b3f10170065713263910">getEpsAngle</a> () const</td></tr>
<tr class="memdesc:a93f67b554b55b3f10170065713263910 inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the epsilon (delta) model angle threshold in radians. <br /></td></tr>
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<tr class="memitem:a514043477fc0efc79aaae0b595cc566c inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a514043477fc0efc79aaae0b595cc566c">segment</a> (<a class="el" href="structpcl_1_1_point_indices.html">PointIndices</a> &amp;inliers, <a class="el" href="structpcl_1_1_model_coefficients.html">ModelCoefficients</a> &amp;model_coefficients)</td></tr>
<tr class="memdesc:a514043477fc0efc79aaae0b595cc566c inherit pub_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Base method for segmentation of a model in a <a class="el" href="classpcl_1_1_point_cloud.html" title="PointCloud represents the base class in PCL for storing collections of 3D points.">PointCloud</a> given by &lt;setInputCloud (), setIndices ()&gt;  <a href="classpcl_1_1_s_a_c_segmentation.html#a514043477fc0efc79aaae0b595cc566c">更多...</a><br /></td></tr>
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<tr class="inherit_header pub_methods_classpcl_1_1_p_c_l_base"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classpcl_1_1_p_c_l_base')"><img src="closed.png" alt="-"/>&#160;Public 成员函数 继承自 <a class="el" href="classpcl_1_1_p_c_l_base.html">pcl::PCLBase&lt; PointT &gt;</a></td></tr>
<tr class="memitem:af4fbc5eb005057f8a0fc6d60bde595df inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="af4fbc5eb005057f8a0fc6d60bde595df"></a>
&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#af4fbc5eb005057f8a0fc6d60bde595df">PCLBase</a> ()</td></tr>
<tr class="memdesc:af4fbc5eb005057f8a0fc6d60bde595df inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Empty constructor. <br /></td></tr>
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<tr class="memitem:a7a6dd7a91275d7737cf1b18005b47244 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="a7a6dd7a91275d7737cf1b18005b47244"></a>
&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#a7a6dd7a91275d7737cf1b18005b47244">PCLBase</a> (const <a class="el" href="classpcl_1_1_p_c_l_base.html">PCLBase</a> &amp;base)</td></tr>
<tr class="memdesc:a7a6dd7a91275d7737cf1b18005b47244 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Copy constructor. <br /></td></tr>
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<tr class="memitem:ad5d6846e98e59c37dcc3dc9958d53966 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="ad5d6846e98e59c37dcc3dc9958d53966"></a>
virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#ad5d6846e98e59c37dcc3dc9958d53966">~PCLBase</a> ()</td></tr>
<tr class="memdesc:ad5d6846e98e59c37dcc3dc9958d53966 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destructor. <br /></td></tr>
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<tr class="memitem:a1952d7101f3942bac3b69ed55c1ca7ea inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#a1952d7101f3942bac3b69ed55c1ca7ea">setInputCloud</a> (const PointCloudConstPtr &amp;cloud)</td></tr>
<tr class="memdesc:a1952d7101f3942bac3b69ed55c1ca7ea inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the input dataset  <a href="classpcl_1_1_p_c_l_base.html#a1952d7101f3942bac3b69ed55c1ca7ea">更多...</a><br /></td></tr>
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<tr class="memitem:a8cd745c4f7a792212f4fc3720b9d46ea inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="a8cd745c4f7a792212f4fc3720b9d46ea"></a>
PointCloudConstPtr const&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#a8cd745c4f7a792212f4fc3720b9d46ea">getInputCloud</a> () const</td></tr>
<tr class="memdesc:a8cd745c4f7a792212f4fc3720b9d46ea inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the input point cloud dataset. <br /></td></tr>
<tr class="separator:a8cd745c4f7a792212f4fc3720b9d46ea inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab219359de6eb34c9d51e2e976dd1a0d1 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#ab219359de6eb34c9d51e2e976dd1a0d1">setIndices</a> (const IndicesPtr &amp;indices)</td></tr>
<tr class="memdesc:ab219359de6eb34c9d51e2e976dd1a0d1 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the vector of indices that represents the input data.  <a href="classpcl_1_1_p_c_l_base.html#ab219359de6eb34c9d51e2e976dd1a0d1">更多...</a><br /></td></tr>
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<tr class="memitem:a436c68c74b31e4dd00000adfbb11ca7c inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#a436c68c74b31e4dd00000adfbb11ca7c">setIndices</a> (const IndicesConstPtr &amp;indices)</td></tr>
<tr class="memdesc:a436c68c74b31e4dd00000adfbb11ca7c inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the vector of indices that represents the input data.  <a href="classpcl_1_1_p_c_l_base.html#a436c68c74b31e4dd00000adfbb11ca7c">更多...</a><br /></td></tr>
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<tr class="memitem:af9cc90d8364ce968566f75800d3773ca inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#af9cc90d8364ce968566f75800d3773ca">setIndices</a> (const PointIndicesConstPtr &amp;indices)</td></tr>
<tr class="memdesc:af9cc90d8364ce968566f75800d3773ca inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the vector of indices that represents the input data.  <a href="classpcl_1_1_p_c_l_base.html#af9cc90d8364ce968566f75800d3773ca">更多...</a><br /></td></tr>
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<tr class="memitem:a930c7a6375fdf65ff8cfdb4eb4a6d996 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#a930c7a6375fdf65ff8cfdb4eb4a6d996">setIndices</a> (size_t row_start, size_t col_start, size_t nb_rows, size_t nb_cols)</td></tr>
<tr class="memdesc:a930c7a6375fdf65ff8cfdb4eb4a6d996 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the indices for the points laying within an interest region of the point cloud.  <a href="classpcl_1_1_p_c_l_base.html#a930c7a6375fdf65ff8cfdb4eb4a6d996">更多...</a><br /></td></tr>
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<tr class="memitem:a058753dd4de73d3d0062fe2e452fba3c inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="a058753dd4de73d3d0062fe2e452fba3c"></a>
IndicesPtr const&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#a058753dd4de73d3d0062fe2e452fba3c">getIndices</a> ()</td></tr>
<tr class="memdesc:a058753dd4de73d3d0062fe2e452fba3c inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the vector of indices used. <br /></td></tr>
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<tr class="memitem:acae187b37230758959572ceb1e6e2045 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="acae187b37230758959572ceb1e6e2045"></a>
IndicesConstPtr const&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#acae187b37230758959572ceb1e6e2045">getIndices</a> () const</td></tr>
<tr class="memdesc:acae187b37230758959572ceb1e6e2045 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the vector of indices used. <br /></td></tr>
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<tr class="memitem:af7335fedb0af0930b9d1dedcb54ba201 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top">const <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#af7335fedb0af0930b9d1dedcb54ba201">operator[]</a> (size_t pos) const</td></tr>
<tr class="memdesc:af7335fedb0af0930b9d1dedcb54ba201 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Override <a class="el" href="classpcl_1_1_point_cloud.html" title="PointCloud represents the base class in PCL for storing collections of 3D points.">PointCloud</a> operator[] to shorten code  <a href="classpcl_1_1_p_c_l_base.html#af7335fedb0af0930b9d1dedcb54ba201">更多...</a><br /></td></tr>
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</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pro-methods"></a>
Protected 成员函数</h2></td></tr>
<tr class="memitem:ac4d61a5778c41a40192d2e44729502a8"><td class="memItemLeft" align="right" valign="top">virtual bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#ac4d61a5778c41a40192d2e44729502a8">initSACModel</a> (const int model_type)</td></tr>
<tr class="memdesc:ac4d61a5778c41a40192d2e44729502a8"><td class="mdescLeft">&#160;</td><td class="mdescRight">Initialize the Sample Consensus model and set its parameters.  <a href="classpcl_1_1_s_a_c_segmentation_from_normals.html#ac4d61a5778c41a40192d2e44729502a8">更多...</a><br /></td></tr>
<tr class="separator:ac4d61a5778c41a40192d2e44729502a8"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a738ce9fb8455174564441597edcd0b9e"><td class="memItemLeft" align="right" valign="top"><a id="a738ce9fb8455174564441597edcd0b9e"></a>
virtual std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">getClassName</a> () const</td></tr>
<tr class="memdesc:a738ce9fb8455174564441597edcd0b9e"><td class="mdescLeft">&#160;</td><td class="mdescRight">Class get name method. <br /></td></tr>
<tr class="separator:a738ce9fb8455174564441597edcd0b9e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pro_methods_classpcl_1_1_s_a_c_segmentation"><td colspan="2" onclick="javascript:toggleInherit('pro_methods_classpcl_1_1_s_a_c_segmentation')"><img src="closed.png" alt="-"/>&#160;Protected 成员函数 继承自 <a class="el" href="classpcl_1_1_s_a_c_segmentation.html">pcl::SACSegmentation&lt; PointT &gt;</a></td></tr>
<tr class="memitem:a2524fe5506c0c43c425dbe492da133ed inherit pro_methods_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a2524fe5506c0c43c425dbe492da133ed">initSAC</a> (const int method_type)</td></tr>
<tr class="memdesc:a2524fe5506c0c43c425dbe492da133ed inherit pro_methods_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Initialize the Sample Consensus method and set its parameters.  <a href="classpcl_1_1_s_a_c_segmentation.html#a2524fe5506c0c43c425dbe492da133ed">更多...</a><br /></td></tr>
<tr class="separator:a2524fe5506c0c43c425dbe492da133ed inherit pro_methods_classpcl_1_1_s_a_c_segmentation"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pro_methods_classpcl_1_1_p_c_l_base"><td colspan="2" onclick="javascript:toggleInherit('pro_methods_classpcl_1_1_p_c_l_base')"><img src="closed.png" alt="-"/>&#160;Protected 成员函数 继承自 <a class="el" href="classpcl_1_1_p_c_l_base.html">pcl::PCLBase&lt; PointT &gt;</a></td></tr>
<tr class="memitem:acceb20854934f4cf77e266eb5a44d4f0 inherit pro_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#acceb20854934f4cf77e266eb5a44d4f0">initCompute</a> ()</td></tr>
<tr class="memdesc:acceb20854934f4cf77e266eb5a44d4f0 inherit pro_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">This method should get called before starting the actual computation.  <a href="classpcl_1_1_p_c_l_base.html#acceb20854934f4cf77e266eb5a44d4f0">更多...</a><br /></td></tr>
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bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#afc426c4eebb94b7734d4fa556bff1420">deinitCompute</a> ()</td></tr>
<tr class="memdesc:afc426c4eebb94b7734d4fa556bff1420 inherit pro_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">This method should get called after finishing the actual computation. <br /></td></tr>
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</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pro-attribs"></a>
Protected 属性</h2></td></tr>
<tr class="memitem:a91b5f388af6d3b9c588f38fcb7a4e4be"><td class="memItemLeft" align="right" valign="top"><a id="a91b5f388af6d3b9c588f38fcb7a4e4be"></a>
PointCloudNConstPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a91b5f388af6d3b9c588f38fcb7a4e4be">normals_</a></td></tr>
<tr class="memdesc:a91b5f388af6d3b9c588f38fcb7a4e4be"><td class="mdescLeft">&#160;</td><td class="mdescRight">A pointer to the input dataset that contains the point normals of the XYZ dataset. <br /></td></tr>
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double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a032a4b4f08619842f7f1c5602b22d9e4">distance_weight_</a></td></tr>
<tr class="memdesc:a032a4b4f08619842f7f1c5602b22d9e4"><td class="mdescLeft">&#160;</td><td class="mdescRight">The relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point normals and the plane normal. <br /></td></tr>
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double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a9757daa415a631f7d4ad088624f4491e">distance_from_origin_</a></td></tr>
<tr class="memdesc:a9757daa415a631f7d4ad088624f4491e"><td class="mdescLeft">&#160;</td><td class="mdescRight">The distance from the template plane to the origin. <br /></td></tr>
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double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a3cd9814bbc521a5f116a1f58cb3cc3d1">min_angle_</a></td></tr>
<tr class="memdesc:a3cd9814bbc521a5f116a1f58cb3cc3d1"><td class="mdescLeft">&#160;</td><td class="mdescRight">The minimum and maximum allowed opening angle of valid cone model. <br /></td></tr>
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double&#160;</td><td class="memItemRight" valign="bottom"><b>max_angle_</b></td></tr>
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<tr class="inherit_header pro_attribs_classpcl_1_1_s_a_c_segmentation"><td colspan="2" onclick="javascript:toggleInherit('pro_attribs_classpcl_1_1_s_a_c_segmentation')"><img src="closed.png" alt="-"/>&#160;Protected 属性 继承自 <a class="el" href="classpcl_1_1_s_a_c_segmentation.html">pcl::SACSegmentation&lt; PointT &gt;</a></td></tr>
<tr class="memitem:a196b024d56223dd122e0a1c23773acab inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="a196b024d56223dd122e0a1c23773acab"></a>
SampleConsensusModelPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a196b024d56223dd122e0a1c23773acab">model_</a></td></tr>
<tr class="memdesc:a196b024d56223dd122e0a1c23773acab inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">The model that needs to be segmented. <br /></td></tr>
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<tr class="memitem:a7e9ad0f4cd31e45c2ff03da17d0c9bce inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="a7e9ad0f4cd31e45c2ff03da17d0c9bce"></a>
SampleConsensusPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a7e9ad0f4cd31e45c2ff03da17d0c9bce">sac_</a></td></tr>
<tr class="memdesc:a7e9ad0f4cd31e45c2ff03da17d0c9bce inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">The sample consensus segmentation method. <br /></td></tr>
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<tr class="memitem:a444d6de9dcabbe20ad1a152bea746dab inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="a444d6de9dcabbe20ad1a152bea746dab"></a>
int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a444d6de9dcabbe20ad1a152bea746dab">model_type_</a></td></tr>
<tr class="memdesc:a444d6de9dcabbe20ad1a152bea746dab inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">The type of model to use (user given parameter). <br /></td></tr>
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<tr class="memitem:af22b2d5e01d6c549b5d7c14caaa28539 inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="af22b2d5e01d6c549b5d7c14caaa28539"></a>
int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#af22b2d5e01d6c549b5d7c14caaa28539">method_type_</a></td></tr>
<tr class="memdesc:af22b2d5e01d6c549b5d7c14caaa28539 inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">The type of sample consensus method to use (user given parameter). <br /></td></tr>
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<tr class="memitem:af262dd025eb187cfc6cb4e638562735a inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="af262dd025eb187cfc6cb4e638562735a"></a>
double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#af262dd025eb187cfc6cb4e638562735a">threshold_</a></td></tr>
<tr class="memdesc:af262dd025eb187cfc6cb4e638562735a inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Distance to the model threshold (user given parameter). <br /></td></tr>
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bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#abe8902ffbc5fd352e38c08f8b9b3601b">optimize_coefficients_</a></td></tr>
<tr class="memdesc:abe8902ffbc5fd352e38c08f8b9b3601b inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set to true if a coefficient refinement is required. <br /></td></tr>
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<tr class="memitem:a873c817931f20ad93869526584c67e22 inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="a873c817931f20ad93869526584c67e22"></a>
double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a873c817931f20ad93869526584c67e22">radius_min_</a></td></tr>
<tr class="memdesc:a873c817931f20ad93869526584c67e22 inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">The minimum and maximum radius limits for the model. Applicable to all models that estimate a radius. <br /></td></tr>
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<tr class="memitem:a1b78e575f1e6eb2b6f32f8c60e777343 inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="a1b78e575f1e6eb2b6f32f8c60e777343"></a>
double&#160;</td><td class="memItemRight" valign="bottom"><b>radius_max_</b></td></tr>
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<tr class="memitem:acfefedfd77b047203d70b9a73c1cbec8 inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="acfefedfd77b047203d70b9a73c1cbec8"></a>
double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#acfefedfd77b047203d70b9a73c1cbec8">samples_radius_</a></td></tr>
<tr class="memdesc:acfefedfd77b047203d70b9a73c1cbec8 inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">The maximum distance of subsequent samples from the first (radius search) <br /></td></tr>
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<tr class="memitem:a8decd0cf3fa904cd8d2530879a7c726b inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="a8decd0cf3fa904cd8d2530879a7c726b"></a>
SearchPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a8decd0cf3fa904cd8d2530879a7c726b">samples_radius_search_</a></td></tr>
<tr class="memdesc:a8decd0cf3fa904cd8d2530879a7c726b inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">The search object for picking subsequent samples using radius search <br /></td></tr>
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<tr class="memitem:ac40b9cd690894f581d507dabbeb89c3c inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="ac40b9cd690894f581d507dabbeb89c3c"></a>
double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#ac40b9cd690894f581d507dabbeb89c3c">eps_angle_</a></td></tr>
<tr class="memdesc:ac40b9cd690894f581d507dabbeb89c3c inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">The maximum allowed difference between the model normal and the given axis. <br /></td></tr>
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<tr class="memitem:abc9924cedf7d0d013f860b8ad3054b69 inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="abc9924cedf7d0d013f860b8ad3054b69"></a>
Eigen::Vector3f&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#abc9924cedf7d0d013f860b8ad3054b69">axis_</a></td></tr>
<tr class="memdesc:abc9924cedf7d0d013f860b8ad3054b69 inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">The axis along which we need to search for a model perpendicular to. <br /></td></tr>
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int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#af99af32608e22a07bc0d8e0cf92d20fb">max_iterations_</a></td></tr>
<tr class="memdesc:af99af32608e22a07bc0d8e0cf92d20fb inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Maximum number of iterations before giving up (user given parameter). <br /></td></tr>
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<tr class="memitem:a29d30627faa3b625702191de4fb3da9b inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="a29d30627faa3b625702191de4fb3da9b"></a>
double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a29d30627faa3b625702191de4fb3da9b">probability_</a></td></tr>
<tr class="memdesc:a29d30627faa3b625702191de4fb3da9b inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Desired probability of choosing at least one sample free from outliers (user given parameter). <br /></td></tr>
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<tr class="memitem:a7e4799ad1df36ce3b56a8c592a67bbf2 inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="memItemLeft" align="right" valign="top"><a id="a7e4799ad1df36ce3b56a8c592a67bbf2"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a7e4799ad1df36ce3b56a8c592a67bbf2">random_</a></td></tr>
<tr class="memdesc:a7e4799ad1df36ce3b56a8c592a67bbf2 inherit pro_attribs_classpcl_1_1_s_a_c_segmentation"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set to true if we need a random seed. <br /></td></tr>
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<tr class="inherit_header pro_attribs_classpcl_1_1_p_c_l_base"><td colspan="2" onclick="javascript:toggleInherit('pro_attribs_classpcl_1_1_p_c_l_base')"><img src="closed.png" alt="-"/>&#160;Protected 属性 继承自 <a class="el" href="classpcl_1_1_p_c_l_base.html">pcl::PCLBase&lt; PointT &gt;</a></td></tr>
<tr class="memitem:a09c70d8e06e3fb4f07903fe6f8d67869 inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="a09c70d8e06e3fb4f07903fe6f8d67869"></a>
PointCloudConstPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a></td></tr>
<tr class="memdesc:a09c70d8e06e3fb4f07903fe6f8d67869 inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">The input point cloud dataset. <br /></td></tr>
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<tr class="memitem:aaee847c8a517ebf365bad2cb182a6626 inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="aaee847c8a517ebf365bad2cb182a6626"></a>
IndicesPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a></td></tr>
<tr class="memdesc:aaee847c8a517ebf365bad2cb182a6626 inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">A pointer to the vector of point indices to use. <br /></td></tr>
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<tr class="memitem:ada1eadb824d34ca9206a86343d9760bb inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="ada1eadb824d34ca9206a86343d9760bb"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#ada1eadb824d34ca9206a86343d9760bb">use_indices_</a></td></tr>
<tr class="memdesc:ada1eadb824d34ca9206a86343d9760bb inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set to true if point indices are used. <br /></td></tr>
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<tr class="memitem:adadb0299f144528020ed558af6879662 inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="adadb0299f144528020ed558af6879662"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#adadb0299f144528020ed558af6879662">fake_indices_</a></td></tr>
<tr class="memdesc:adadb0299f144528020ed558af6879662 inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">If no set of indices are given, we construct a set of fake indices that mimic the input <a class="el" href="classpcl_1_1_point_cloud.html" title="PointCloud represents the base class in PCL for storing collections of 3D points.">PointCloud</a>. <br /></td></tr>
<tr class="separator:adadb0299f144528020ed558af6879662 inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
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<a name="details" id="details"></a><h2 class="groupheader">详细描述</h2>
<div class="textblock"><h3>template&lt;typename PointT, typename PointNT&gt;<br />
class pcl::SACSegmentationFromNormals&lt; PointT, PointNT &gt;</h3>

<p><b><a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html" title="SACSegmentationFromNormals represents the PCL nodelet segmentation class for Sample Consensus methods...">SACSegmentationFromNormals</a></b> represents the PCL nodelet segmentation class for Sample Consensus methods and models that require the use of surface normals for estimation. </p>
</div><h2 class="groupheader">构造及析构函数说明</h2>
<a id="a6c3a8db014d9ebb9388886888e7389db"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a6c3a8db014d9ebb9388886888e7389db">&#9670;&nbsp;</a></span>SACSegmentationFromNormals()</h2>

<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;typename PointT , typename PointNT &gt; </div>
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          <td class="memname"><a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html">pcl::SACSegmentationFromNormals</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a>, PointNT &gt;::<a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html">SACSegmentationFromNormals</a> </td>
          <td>(</td>
          <td class="paramtype">bool&#160;</td>
          <td class="paramname"><em>random</em> = <code>false</code></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">inline</span></span>  </td>
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</div><div class="memdoc">

<p>Empty constructor. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">random</td><td>if true set the random seed to the current time, else set to 12345 (default: false) </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160;        : SACSegmentation&lt;PointT&gt; (random)</div>
<div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160;        , <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a91b5f388af6d3b9c588f38fcb7a4e4be">normals_</a> ()</div>
<div class="line"><a name="l00343"></a><span class="lineno">  343</span>&#160;        , <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a032a4b4f08619842f7f1c5602b22d9e4">distance_weight_</a> (0.1)</div>
<div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;        , <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a9757daa415a631f7d4ad088624f4491e">distance_from_origin_</a> (0)</div>
<div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160;        , <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a3cd9814bbc521a5f116a1f58cb3cc3d1">min_angle_</a> ()</div>
<div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160;        , max_angle_ ()</div>
<div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;      {};</div>
<div class="ttc" id="aclasspcl_1_1_s_a_c_segmentation_from_normals_html_a032a4b4f08619842f7f1c5602b22d9e4"><div class="ttname"><a href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a032a4b4f08619842f7f1c5602b22d9e4">pcl::SACSegmentationFromNormals::distance_weight_</a></div><div class="ttdeci">double distance_weight_</div><div class="ttdoc">The relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point norma...</div><div class="ttdef"><b>Definition:</b> sac_segmentation.h:408</div></div>
<div class="ttc" id="aclasspcl_1_1_s_a_c_segmentation_from_normals_html_a3cd9814bbc521a5f116a1f58cb3cc3d1"><div class="ttname"><a href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a3cd9814bbc521a5f116a1f58cb3cc3d1">pcl::SACSegmentationFromNormals::min_angle_</a></div><div class="ttdeci">double min_angle_</div><div class="ttdoc">The minimum and maximum allowed opening angle of valid cone model.</div><div class="ttdef"><b>Definition:</b> sac_segmentation.h:414</div></div>
<div class="ttc" id="aclasspcl_1_1_s_a_c_segmentation_from_normals_html_a91b5f388af6d3b9c588f38fcb7a4e4be"><div class="ttname"><a href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a91b5f388af6d3b9c588f38fcb7a4e4be">pcl::SACSegmentationFromNormals::normals_</a></div><div class="ttdeci">PointCloudNConstPtr normals_</div><div class="ttdoc">A pointer to the input dataset that contains the point normals of the XYZ dataset.</div><div class="ttdef"><b>Definition:</b> sac_segmentation.h:403</div></div>
<div class="ttc" id="aclasspcl_1_1_s_a_c_segmentation_from_normals_html_a9757daa415a631f7d4ad088624f4491e"><div class="ttname"><a href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a9757daa415a631f7d4ad088624f4491e">pcl::SACSegmentationFromNormals::distance_from_origin_</a></div><div class="ttdeci">double distance_from_origin_</div><div class="ttdoc">The distance from the template plane to the origin.</div><div class="ttdef"><b>Definition:</b> sac_segmentation.h:411</div></div>
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</div>
<h2 class="groupheader">成员函数说明</h2>
<a id="ac4d61a5778c41a40192d2e44729502a8"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ac4d61a5778c41a40192d2e44729502a8">&#9670;&nbsp;</a></span>initSACModel()</h2>

<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;typename PointT , typename PointNT &gt; </div>
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  <tr>
  <td class="mlabels-left">
      <table class="memname">
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          <td class="memname">bool <a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html">pcl::SACSegmentationFromNormals</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a>, PointNT &gt;::initSACModel </td>
          <td>(</td>
          <td class="paramtype">const int&#160;</td>
          <td class="paramname"><em>model_type</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">protected</span><span class="mlabel">virtual</span></span>  </td>
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<p>Initialize the Sample Consensus model and set its parameters. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">model_type</td><td>the type of SAC model that is to be used </td></tr>
  </table>
  </dd>
</dl>

<p>重载 <a class="el" href="classpcl_1_1_s_a_c_segmentation.html#a73f671838c3ec8c0f08a3c78a7cac80b">pcl::SACSegmentation&lt; PointT &gt;</a> .</p>
<div class="fragment"><div class="line"><a name="l00343"></a><span class="lineno">  343</span>&#160;{</div>
<div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;  <span class="keywordflow">if</span> (!<a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a> || !<a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a91b5f388af6d3b9c588f38fcb7a4e4be">normals_</a>)</div>
<div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160;  {</div>
<div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::%s::initSACModel] Input data (XYZ or normals) not given! Cannot continue.\n&quot;</span>, <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">getClassName</a> ().c_str ());</div>
<div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;    <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00348"></a><span class="lineno">  348</span>&#160;  }</div>
<div class="line"><a name="l00349"></a><span class="lineno">  349</span>&#160;  <span class="comment">// Check if input is synced with the normals</span></div>
<div class="line"><a name="l00350"></a><span class="lineno">  350</span>&#160;  <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>-&gt;points.size () != <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a91b5f388af6d3b9c588f38fcb7a4e4be">normals_</a>-&gt;points.size ())</div>
<div class="line"><a name="l00351"></a><span class="lineno">  351</span>&#160;  {</div>
<div class="line"><a name="l00352"></a><span class="lineno">  352</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::%s::initSACModel] The number of points inthe input point cloud differs than the number of points in the normals!\n&quot;</span>, <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">getClassName</a> ().c_str ());</div>
<div class="line"><a name="l00353"></a><span class="lineno">  353</span>&#160;    <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160;  }</div>
<div class="line"><a name="l00355"></a><span class="lineno">  355</span>&#160; </div>
<div class="line"><a name="l00356"></a><span class="lineno">  356</span>&#160;  <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1_s_a_c_segmentation.html#a196b024d56223dd122e0a1c23773acab">model_</a>)</div>
<div class="line"><a name="l00357"></a><span class="lineno">  357</span>&#160;    <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#a196b024d56223dd122e0a1c23773acab">model_</a>.reset ();</div>
<div class="line"><a name="l00358"></a><span class="lineno">  358</span>&#160; </div>
<div class="line"><a name="l00359"></a><span class="lineno">  359</span>&#160;  <span class="comment">// Build the model</span></div>
<div class="line"><a name="l00360"></a><span class="lineno">  360</span>&#160;  <span class="keywordflow">switch</span> (model_type)</div>
<div class="line"><a name="l00361"></a><span class="lineno">  361</span>&#160;  {</div>
<div class="line"><a name="l00362"></a><span class="lineno">  362</span>&#160;    <span class="keywordflow">case</span> SACMODEL_CYLINDER:</div>
<div class="line"><a name="l00363"></a><span class="lineno">  363</span>&#160;    {</div>
<div class="line"><a name="l00364"></a><span class="lineno">  364</span>&#160;      PCL_DEBUG (<span class="stringliteral">&quot;[pcl::%s::initSACModel] Using a model of type: SACMODEL_CYLINDER\n&quot;</span>, <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">getClassName</a> ().c_str ());</div>
<div class="line"><a name="l00365"></a><span class="lineno">  365</span>&#160;      <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#a196b024d56223dd122e0a1c23773acab">model_</a>.reset (<span class="keyword">new</span> SampleConsensusModelCylinder&lt;PointT, PointNT &gt; (<a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>, *<a class="code" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a>, <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#a7e4799ad1df36ce3b56a8c592a67bbf2">random_</a>));</div>
<div class="line"><a name="l00366"></a><span class="lineno">  366</span>&#160;      <span class="keyword">typename</span> SampleConsensusModelCylinder&lt;PointT, PointNT&gt;::Ptr model_cylinder = boost::static_pointer_cast&lt;SampleConsensusModelCylinder&lt;PointT, PointNT&gt; &gt; (<a class="code" href="classpcl_1_1_s_a_c_segmentation.html#a196b024d56223dd122e0a1c23773acab">model_</a>);</div>
<div class="line"><a name="l00367"></a><span class="lineno">  367</span>&#160; </div>
<div class="line"><a name="l00368"></a><span class="lineno">  368</span>&#160;      <span class="comment">// Set the input normals</span></div>
<div class="line"><a name="l00369"></a><span class="lineno">  369</span>&#160;      model_cylinder-&gt;setInputNormals (<a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a91b5f388af6d3b9c588f38fcb7a4e4be">normals_</a>);</div>
<div class="line"><a name="l00370"></a><span class="lineno">  370</span>&#160;      <span class="keywordtype">double</span> min_radius, max_radius;</div>
<div class="line"><a name="l00371"></a><span class="lineno">  371</span>&#160;      model_cylinder-&gt;getRadiusLimits (min_radius, max_radius);</div>
<div class="line"><a name="l00372"></a><span class="lineno">  372</span>&#160;      <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1_s_a_c_segmentation.html#a873c817931f20ad93869526584c67e22">radius_min_</a> != min_radius &amp;&amp; radius_max_ != max_radius)</div>
<div class="line"><a name="l00373"></a><span class="lineno">  373</span>&#160;      {</div>
<div class="line"><a name="l00374"></a><span class="lineno">  374</span>&#160;        PCL_DEBUG (<span class="stringliteral">&quot;[pcl::%s::initSACModel] Setting radius limits to %f/%f\n&quot;</span>, <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">getClassName</a> ().c_str (), <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#a873c817931f20ad93869526584c67e22">radius_min_</a>, radius_max_);</div>
<div class="line"><a name="l00375"></a><span class="lineno">  375</span>&#160;        model_cylinder-&gt;setRadiusLimits (<a class="code" href="classpcl_1_1_s_a_c_segmentation.html#a873c817931f20ad93869526584c67e22">radius_min_</a>, radius_max_);</div>
<div class="line"><a name="l00376"></a><span class="lineno">  376</span>&#160;      }</div>
<div class="line"><a name="l00377"></a><span class="lineno">  377</span>&#160;      <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a032a4b4f08619842f7f1c5602b22d9e4">distance_weight_</a> != model_cylinder-&gt;getNormalDistanceWeight ())</div>
<div class="line"><a name="l00378"></a><span class="lineno">  378</span>&#160;      {</div>
<div class="line"><a name="l00379"></a><span class="lineno">  379</span>&#160;        PCL_DEBUG (<span class="stringliteral">&quot;[pcl::%s::initSACModel] Setting normal distance weight to %f\n&quot;</span>, <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">getClassName</a> ().c_str (), <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a032a4b4f08619842f7f1c5602b22d9e4">distance_weight_</a>);</div>
<div class="line"><a name="l00380"></a><span class="lineno">  380</span>&#160;        model_cylinder-&gt;setNormalDistanceWeight (<a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a032a4b4f08619842f7f1c5602b22d9e4">distance_weight_</a>);</div>
<div class="line"><a name="l00381"></a><span class="lineno">  381</span>&#160;      }</div>
<div class="line"><a name="l00382"></a><span class="lineno">  382</span>&#160;      <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1_s_a_c_segmentation.html#abc9924cedf7d0d013f860b8ad3054b69">axis_</a> != Eigen::Vector3f::Zero () &amp;&amp; model_cylinder-&gt;getAxis () != <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#abc9924cedf7d0d013f860b8ad3054b69">axis_</a>)</div>
<div class="line"><a name="l00383"></a><span class="lineno">  383</span>&#160;      {</div>
<div class="line"><a name="l00384"></a><span class="lineno">  384</span>&#160;        PCL_DEBUG (<span class="stringliteral">&quot;[pcl::%s::initSACModel] Setting the axis to %f, %f, %f\n&quot;</span>, <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">getClassName</a> ().c_str (), <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#abc9924cedf7d0d013f860b8ad3054b69">axis_</a>[0], <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#abc9924cedf7d0d013f860b8ad3054b69">axis_</a>[1], <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#abc9924cedf7d0d013f860b8ad3054b69">axis_</a>[2]);</div>
<div class="line"><a name="l00385"></a><span class="lineno">  385</span>&#160;        model_cylinder-&gt;setAxis (<a class="code" href="classpcl_1_1_s_a_c_segmentation.html#abc9924cedf7d0d013f860b8ad3054b69">axis_</a>);</div>
<div class="line"><a name="l00386"></a><span class="lineno">  386</span>&#160;      }</div>
<div class="line"><a name="l00387"></a><span class="lineno">  387</span>&#160;      <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1_s_a_c_segmentation.html#ac40b9cd690894f581d507dabbeb89c3c">eps_angle_</a> != 0.0 &amp;&amp; model_cylinder-&gt;getEpsAngle () != <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#ac40b9cd690894f581d507dabbeb89c3c">eps_angle_</a>)</div>
<div class="line"><a name="l00388"></a><span class="lineno">  388</span>&#160;      {</div>
<div class="line"><a name="l00389"></a><span class="lineno">  389</span>&#160;        PCL_DEBUG (<span class="stringliteral">&quot;[pcl::%s::initSACModel] Setting the epsilon angle to %f (%f degrees)\n&quot;</span>, <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">getClassName</a> ().c_str (), <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#ac40b9cd690894f581d507dabbeb89c3c">eps_angle_</a>, <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#ac40b9cd690894f581d507dabbeb89c3c">eps_angle_</a> * 180.0 / M_PI);</div>
<div class="line"><a name="l00390"></a><span class="lineno">  390</span>&#160;        model_cylinder-&gt;setEpsAngle (<a class="code" href="classpcl_1_1_s_a_c_segmentation.html#ac40b9cd690894f581d507dabbeb89c3c">eps_angle_</a>);</div>
<div class="line"><a name="l00391"></a><span class="lineno">  391</span>&#160;      }</div>
<div class="line"><a name="l00392"></a><span class="lineno">  392</span>&#160;      <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00393"></a><span class="lineno">  393</span>&#160;    }</div>
<div class="line"><a name="l00394"></a><span class="lineno">  394</span>&#160;    <span class="keywordflow">case</span> SACMODEL_NORMAL_PLANE:</div>
<div class="line"><a name="l00395"></a><span class="lineno">  395</span>&#160;    {</div>
<div class="line"><a name="l00396"></a><span class="lineno">  396</span>&#160;      PCL_DEBUG (<span class="stringliteral">&quot;[pcl::%s::initSACModel] Using a model of type: SACMODEL_NORMAL_PLANE\n&quot;</span>, <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">getClassName</a> ().c_str ());</div>
<div class="line"><a name="l00397"></a><span class="lineno">  397</span>&#160;      <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#a196b024d56223dd122e0a1c23773acab">model_</a>.reset (<span class="keyword">new</span> SampleConsensusModelNormalPlane&lt;PointT, PointNT&gt; (<a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>, *<a class="code" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a>, <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#a7e4799ad1df36ce3b56a8c592a67bbf2">random_</a>));</div>
<div class="line"><a name="l00398"></a><span class="lineno">  398</span>&#160;      <span class="keyword">typename</span> SampleConsensusModelNormalPlane&lt;PointT, PointNT&gt;::Ptr model_normals = boost::static_pointer_cast&lt;SampleConsensusModelNormalPlane&lt;PointT, PointNT&gt; &gt; (<a class="code" href="classpcl_1_1_s_a_c_segmentation.html#a196b024d56223dd122e0a1c23773acab">model_</a>);</div>
<div class="line"><a name="l00399"></a><span class="lineno">  399</span>&#160;      <span class="comment">// Set the input normals</span></div>
<div class="line"><a name="l00400"></a><span class="lineno">  400</span>&#160;      model_normals-&gt;setInputNormals (<a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a91b5f388af6d3b9c588f38fcb7a4e4be">normals_</a>);</div>
<div class="line"><a name="l00401"></a><span class="lineno">  401</span>&#160;      <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a032a4b4f08619842f7f1c5602b22d9e4">distance_weight_</a> != model_normals-&gt;getNormalDistanceWeight ())</div>
<div class="line"><a name="l00402"></a><span class="lineno">  402</span>&#160;      {</div>
<div class="line"><a name="l00403"></a><span class="lineno">  403</span>&#160;        PCL_DEBUG (<span class="stringliteral">&quot;[pcl::%s::initSACModel] Setting normal distance weight to %f\n&quot;</span>, <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">getClassName</a> ().c_str (), <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a032a4b4f08619842f7f1c5602b22d9e4">distance_weight_</a>);</div>
<div class="line"><a name="l00404"></a><span class="lineno">  404</span>&#160;        model_normals-&gt;setNormalDistanceWeight (<a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a032a4b4f08619842f7f1c5602b22d9e4">distance_weight_</a>);</div>
<div class="line"><a name="l00405"></a><span class="lineno">  405</span>&#160;      }</div>
<div class="line"><a name="l00406"></a><span class="lineno">  406</span>&#160;      <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00407"></a><span class="lineno">  407</span>&#160;    }</div>
<div class="line"><a name="l00408"></a><span class="lineno">  408</span>&#160;    <span class="keywordflow">case</span> SACMODEL_NORMAL_PARALLEL_PLANE:</div>
<div class="line"><a name="l00409"></a><span class="lineno">  409</span>&#160;    {</div>
<div class="line"><a name="l00410"></a><span class="lineno">  410</span>&#160;      PCL_DEBUG (<span class="stringliteral">&quot;[pcl::%s::initSACModel] Using a model of type: SACMODEL_NORMAL_PARALLEL_PLANE\n&quot;</span>, <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">getClassName</a> ().c_str ());</div>
<div class="line"><a name="l00411"></a><span class="lineno">  411</span>&#160;      <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#a196b024d56223dd122e0a1c23773acab">model_</a>.reset (<span class="keyword">new</span> SampleConsensusModelNormalParallelPlane&lt;PointT, PointNT&gt; (<a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>, *<a class="code" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a>, <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#a7e4799ad1df36ce3b56a8c592a67bbf2">random_</a>));</div>
<div class="line"><a name="l00412"></a><span class="lineno">  412</span>&#160;      <span class="keyword">typename</span> SampleConsensusModelNormalParallelPlane&lt;PointT, PointNT&gt;::Ptr model_normals = boost::static_pointer_cast&lt;SampleConsensusModelNormalParallelPlane&lt;PointT, PointNT&gt; &gt; (<a class="code" href="classpcl_1_1_s_a_c_segmentation.html#a196b024d56223dd122e0a1c23773acab">model_</a>);</div>
<div class="line"><a name="l00413"></a><span class="lineno">  413</span>&#160;      <span class="comment">// Set the input normals</span></div>
<div class="line"><a name="l00414"></a><span class="lineno">  414</span>&#160;      model_normals-&gt;setInputNormals (<a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a91b5f388af6d3b9c588f38fcb7a4e4be">normals_</a>);</div>
<div class="line"><a name="l00415"></a><span class="lineno">  415</span>&#160;      <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a032a4b4f08619842f7f1c5602b22d9e4">distance_weight_</a> != model_normals-&gt;getNormalDistanceWeight ())</div>
<div class="line"><a name="l00416"></a><span class="lineno">  416</span>&#160;      {</div>
<div class="line"><a name="l00417"></a><span class="lineno">  417</span>&#160;        PCL_DEBUG (<span class="stringliteral">&quot;[pcl::%s::initSACModel] Setting normal distance weight to %f\n&quot;</span>, <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">getClassName</a> ().c_str (), <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a032a4b4f08619842f7f1c5602b22d9e4">distance_weight_</a>);</div>
<div class="line"><a name="l00418"></a><span class="lineno">  418</span>&#160;        model_normals-&gt;setNormalDistanceWeight (<a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a032a4b4f08619842f7f1c5602b22d9e4">distance_weight_</a>);</div>
<div class="line"><a name="l00419"></a><span class="lineno">  419</span>&#160;      }</div>
<div class="line"><a name="l00420"></a><span class="lineno">  420</span>&#160;      <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a9757daa415a631f7d4ad088624f4491e">distance_from_origin_</a> != model_normals-&gt;getDistanceFromOrigin ())</div>
<div class="line"><a name="l00421"></a><span class="lineno">  421</span>&#160;      {</div>
<div class="line"><a name="l00422"></a><span class="lineno">  422</span>&#160;        PCL_DEBUG (<span class="stringliteral">&quot;[pcl::%s::initSACModel] Setting the distance to origin to %f\n&quot;</span>, <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">getClassName</a> ().c_str (), <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a9757daa415a631f7d4ad088624f4491e">distance_from_origin_</a>);</div>
<div class="line"><a name="l00423"></a><span class="lineno">  423</span>&#160;        model_normals-&gt;setDistanceFromOrigin (<a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a9757daa415a631f7d4ad088624f4491e">distance_from_origin_</a>);</div>
<div class="line"><a name="l00424"></a><span class="lineno">  424</span>&#160;      }</div>
<div class="line"><a name="l00425"></a><span class="lineno">  425</span>&#160;      <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1_s_a_c_segmentation.html#abc9924cedf7d0d013f860b8ad3054b69">axis_</a> != Eigen::Vector3f::Zero () &amp;&amp; model_normals-&gt;getAxis () != <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#abc9924cedf7d0d013f860b8ad3054b69">axis_</a>)</div>
<div class="line"><a name="l00426"></a><span class="lineno">  426</span>&#160;      {</div>
<div class="line"><a name="l00427"></a><span class="lineno">  427</span>&#160;        PCL_DEBUG (<span class="stringliteral">&quot;[pcl::%s::initSACModel] Setting the axis to %f, %f, %f\n&quot;</span>, <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">getClassName</a> ().c_str (), <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#abc9924cedf7d0d013f860b8ad3054b69">axis_</a>[0], <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#abc9924cedf7d0d013f860b8ad3054b69">axis_</a>[1], <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#abc9924cedf7d0d013f860b8ad3054b69">axis_</a>[2]);</div>
<div class="line"><a name="l00428"></a><span class="lineno">  428</span>&#160;        model_normals-&gt;setAxis (<a class="code" href="classpcl_1_1_s_a_c_segmentation.html#abc9924cedf7d0d013f860b8ad3054b69">axis_</a>);</div>
<div class="line"><a name="l00429"></a><span class="lineno">  429</span>&#160;      }</div>
<div class="line"><a name="l00430"></a><span class="lineno">  430</span>&#160;      <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1_s_a_c_segmentation.html#ac40b9cd690894f581d507dabbeb89c3c">eps_angle_</a> != 0.0 &amp;&amp; model_normals-&gt;getEpsAngle () != <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#ac40b9cd690894f581d507dabbeb89c3c">eps_angle_</a>)</div>
<div class="line"><a name="l00431"></a><span class="lineno">  431</span>&#160;      {</div>
<div class="line"><a name="l00432"></a><span class="lineno">  432</span>&#160;        PCL_DEBUG (<span class="stringliteral">&quot;[pcl::%s::initSACModel] Setting the epsilon angle to %f (%f degrees)\n&quot;</span>, <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">getClassName</a> ().c_str (), <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#ac40b9cd690894f581d507dabbeb89c3c">eps_angle_</a>, <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#ac40b9cd690894f581d507dabbeb89c3c">eps_angle_</a> * 180.0 / M_PI);</div>
<div class="line"><a name="l00433"></a><span class="lineno">  433</span>&#160;        model_normals-&gt;setEpsAngle (<a class="code" href="classpcl_1_1_s_a_c_segmentation.html#ac40b9cd690894f581d507dabbeb89c3c">eps_angle_</a>);</div>
<div class="line"><a name="l00434"></a><span class="lineno">  434</span>&#160;      }</div>
<div class="line"><a name="l00435"></a><span class="lineno">  435</span>&#160;      <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00436"></a><span class="lineno">  436</span>&#160;    }</div>
<div class="line"><a name="l00437"></a><span class="lineno">  437</span>&#160;    <span class="keywordflow">case</span> SACMODEL_CONE:</div>
<div class="line"><a name="l00438"></a><span class="lineno">  438</span>&#160;    {</div>
<div class="line"><a name="l00439"></a><span class="lineno">  439</span>&#160;      PCL_DEBUG (<span class="stringliteral">&quot;[pcl::%s::initSACModel] Using a model of type: SACMODEL_CONE\n&quot;</span>, <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">getClassName</a> ().c_str ());</div>
<div class="line"><a name="l00440"></a><span class="lineno">  440</span>&#160;      <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#a196b024d56223dd122e0a1c23773acab">model_</a>.reset (<span class="keyword">new</span> SampleConsensusModelCone&lt;PointT, PointNT&gt; (<a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>, *<a class="code" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a>, <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#a7e4799ad1df36ce3b56a8c592a67bbf2">random_</a>));</div>
<div class="line"><a name="l00441"></a><span class="lineno">  441</span>&#160;      <span class="keyword">typename</span> SampleConsensusModelCone&lt;PointT, PointNT&gt;::Ptr model_cone = boost::static_pointer_cast&lt;SampleConsensusModelCone&lt;PointT, PointNT&gt; &gt; (<a class="code" href="classpcl_1_1_s_a_c_segmentation.html#a196b024d56223dd122e0a1c23773acab">model_</a>);</div>
<div class="line"><a name="l00442"></a><span class="lineno">  442</span>&#160; </div>
<div class="line"><a name="l00443"></a><span class="lineno">  443</span>&#160;      <span class="comment">// Set the input normals</span></div>
<div class="line"><a name="l00444"></a><span class="lineno">  444</span>&#160;      model_cone-&gt;setInputNormals (<a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a91b5f388af6d3b9c588f38fcb7a4e4be">normals_</a>);</div>
<div class="line"><a name="l00445"></a><span class="lineno">  445</span>&#160;      <span class="keywordtype">double</span> min_angle, max_angle;</div>
<div class="line"><a name="l00446"></a><span class="lineno">  446</span>&#160;      model_cone-&gt;getMinMaxOpeningAngle(min_angle, max_angle);</div>
<div class="line"><a name="l00447"></a><span class="lineno">  447</span>&#160;      <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a3cd9814bbc521a5f116a1f58cb3cc3d1">min_angle_</a> != min_angle &amp;&amp; max_angle_ != max_angle)</div>
<div class="line"><a name="l00448"></a><span class="lineno">  448</span>&#160;      {</div>
<div class="line"><a name="l00449"></a><span class="lineno">  449</span>&#160;        PCL_DEBUG (<span class="stringliteral">&quot;[pcl::%s::initSACModel] Setting minimum and maximum opening angle to %f and %f \n&quot;</span>, <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">getClassName</a> ().c_str (), <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a3cd9814bbc521a5f116a1f58cb3cc3d1">min_angle_</a>, max_angle_);</div>
<div class="line"><a name="l00450"></a><span class="lineno">  450</span>&#160;        model_cone-&gt;setMinMaxOpeningAngle (<a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a3cd9814bbc521a5f116a1f58cb3cc3d1">min_angle_</a>, max_angle_);</div>
<div class="line"><a name="l00451"></a><span class="lineno">  451</span>&#160;      }</div>
<div class="line"><a name="l00452"></a><span class="lineno">  452</span>&#160; </div>
<div class="line"><a name="l00453"></a><span class="lineno">  453</span>&#160;      <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a032a4b4f08619842f7f1c5602b22d9e4">distance_weight_</a> != model_cone-&gt;getNormalDistanceWeight ())</div>
<div class="line"><a name="l00454"></a><span class="lineno">  454</span>&#160;      {</div>
<div class="line"><a name="l00455"></a><span class="lineno">  455</span>&#160;        PCL_DEBUG (<span class="stringliteral">&quot;[pcl::%s::initSACModel] Setting normal distance weight to %f\n&quot;</span>, <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">getClassName</a> ().c_str (), <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a032a4b4f08619842f7f1c5602b22d9e4">distance_weight_</a>);</div>
<div class="line"><a name="l00456"></a><span class="lineno">  456</span>&#160;        model_cone-&gt;setNormalDistanceWeight (<a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a032a4b4f08619842f7f1c5602b22d9e4">distance_weight_</a>);</div>
<div class="line"><a name="l00457"></a><span class="lineno">  457</span>&#160;      }</div>
<div class="line"><a name="l00458"></a><span class="lineno">  458</span>&#160;      <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1_s_a_c_segmentation.html#abc9924cedf7d0d013f860b8ad3054b69">axis_</a> != Eigen::Vector3f::Zero () &amp;&amp; model_cone-&gt;getAxis () != <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#abc9924cedf7d0d013f860b8ad3054b69">axis_</a>)</div>
<div class="line"><a name="l00459"></a><span class="lineno">  459</span>&#160;      {</div>
<div class="line"><a name="l00460"></a><span class="lineno">  460</span>&#160;        PCL_DEBUG (<span class="stringliteral">&quot;[pcl::%s::initSACModel] Setting the axis to %f, %f, %f\n&quot;</span>, <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">getClassName</a> ().c_str (), <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#abc9924cedf7d0d013f860b8ad3054b69">axis_</a>[0], <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#abc9924cedf7d0d013f860b8ad3054b69">axis_</a>[1], <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#abc9924cedf7d0d013f860b8ad3054b69">axis_</a>[2]);</div>
<div class="line"><a name="l00461"></a><span class="lineno">  461</span>&#160;        model_cone-&gt;setAxis (<a class="code" href="classpcl_1_1_s_a_c_segmentation.html#abc9924cedf7d0d013f860b8ad3054b69">axis_</a>);</div>
<div class="line"><a name="l00462"></a><span class="lineno">  462</span>&#160;      }</div>
<div class="line"><a name="l00463"></a><span class="lineno">  463</span>&#160;      <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1_s_a_c_segmentation.html#ac40b9cd690894f581d507dabbeb89c3c">eps_angle_</a> != 0.0 &amp;&amp; model_cone-&gt;getEpsAngle () != <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#ac40b9cd690894f581d507dabbeb89c3c">eps_angle_</a>)</div>
<div class="line"><a name="l00464"></a><span class="lineno">  464</span>&#160;      {</div>
<div class="line"><a name="l00465"></a><span class="lineno">  465</span>&#160;        PCL_DEBUG (<span class="stringliteral">&quot;[pcl::%s::initSACModel] Setting the epsilon angle to %f (%f degrees)\n&quot;</span>, <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">getClassName</a> ().c_str (), <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#ac40b9cd690894f581d507dabbeb89c3c">eps_angle_</a>, <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#ac40b9cd690894f581d507dabbeb89c3c">eps_angle_</a> * 180.0 / M_PI);</div>
<div class="line"><a name="l00466"></a><span class="lineno">  466</span>&#160;        model_cone-&gt;setEpsAngle (<a class="code" href="classpcl_1_1_s_a_c_segmentation.html#ac40b9cd690894f581d507dabbeb89c3c">eps_angle_</a>);</div>
<div class="line"><a name="l00467"></a><span class="lineno">  467</span>&#160;      }</div>
<div class="line"><a name="l00468"></a><span class="lineno">  468</span>&#160;      <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00469"></a><span class="lineno">  469</span>&#160;    }</div>
<div class="line"><a name="l00470"></a><span class="lineno">  470</span>&#160;    <span class="keywordflow">case</span> SACMODEL_NORMAL_SPHERE:</div>
<div class="line"><a name="l00471"></a><span class="lineno">  471</span>&#160;    {</div>
<div class="line"><a name="l00472"></a><span class="lineno">  472</span>&#160;      PCL_DEBUG (<span class="stringliteral">&quot;[pcl::%s::initSACModel] Using a model of type: SACMODEL_NORMAL_SPHERE\n&quot;</span>, <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">getClassName</a> ().c_str ());</div>
<div class="line"><a name="l00473"></a><span class="lineno">  473</span>&#160;      <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#a196b024d56223dd122e0a1c23773acab">model_</a>.reset (<span class="keyword">new</span> SampleConsensusModelNormalSphere&lt;PointT, PointNT&gt; (<a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>, *<a class="code" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a>, <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#a7e4799ad1df36ce3b56a8c592a67bbf2">random_</a>));</div>
<div class="line"><a name="l00474"></a><span class="lineno">  474</span>&#160;      <span class="keyword">typename</span> SampleConsensusModelNormalSphere&lt;PointT, PointNT&gt;::Ptr model_normals_sphere = boost::static_pointer_cast&lt;SampleConsensusModelNormalSphere&lt;PointT, PointNT&gt; &gt; (<a class="code" href="classpcl_1_1_s_a_c_segmentation.html#a196b024d56223dd122e0a1c23773acab">model_</a>);</div>
<div class="line"><a name="l00475"></a><span class="lineno">  475</span>&#160;      <span class="comment">// Set the input normals</span></div>
<div class="line"><a name="l00476"></a><span class="lineno">  476</span>&#160;      model_normals_sphere-&gt;setInputNormals (<a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a91b5f388af6d3b9c588f38fcb7a4e4be">normals_</a>);</div>
<div class="line"><a name="l00477"></a><span class="lineno">  477</span>&#160;      <span class="keywordtype">double</span> min_radius, max_radius;</div>
<div class="line"><a name="l00478"></a><span class="lineno">  478</span>&#160;      model_normals_sphere-&gt;getRadiusLimits (min_radius, max_radius);</div>
<div class="line"><a name="l00479"></a><span class="lineno">  479</span>&#160;      <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1_s_a_c_segmentation.html#a873c817931f20ad93869526584c67e22">radius_min_</a> != min_radius &amp;&amp; radius_max_ != max_radius)</div>
<div class="line"><a name="l00480"></a><span class="lineno">  480</span>&#160;      {</div>
<div class="line"><a name="l00481"></a><span class="lineno">  481</span>&#160;        PCL_DEBUG (<span class="stringliteral">&quot;[pcl::%s::initSACModel] Setting radius limits to %f/%f\n&quot;</span>, <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">getClassName</a> ().c_str (), <a class="code" href="classpcl_1_1_s_a_c_segmentation.html#a873c817931f20ad93869526584c67e22">radius_min_</a>, radius_max_);</div>
<div class="line"><a name="l00482"></a><span class="lineno">  482</span>&#160;        model_normals_sphere-&gt;setRadiusLimits (<a class="code" href="classpcl_1_1_s_a_c_segmentation.html#a873c817931f20ad93869526584c67e22">radius_min_</a>, radius_max_);</div>
<div class="line"><a name="l00483"></a><span class="lineno">  483</span>&#160;      }</div>
<div class="line"><a name="l00484"></a><span class="lineno">  484</span>&#160; </div>
<div class="line"><a name="l00485"></a><span class="lineno">  485</span>&#160;      <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a032a4b4f08619842f7f1c5602b22d9e4">distance_weight_</a> != model_normals_sphere-&gt;getNormalDistanceWeight ())</div>
<div class="line"><a name="l00486"></a><span class="lineno">  486</span>&#160;      {</div>
<div class="line"><a name="l00487"></a><span class="lineno">  487</span>&#160;        PCL_DEBUG (<span class="stringliteral">&quot;[pcl::%s::initSACModel] Setting normal distance weight to %f\n&quot;</span>, <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">getClassName</a> ().c_str (), <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a032a4b4f08619842f7f1c5602b22d9e4">distance_weight_</a>);</div>
<div class="line"><a name="l00488"></a><span class="lineno">  488</span>&#160;        model_normals_sphere-&gt;setNormalDistanceWeight (<a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a032a4b4f08619842f7f1c5602b22d9e4">distance_weight_</a>);</div>
<div class="line"><a name="l00489"></a><span class="lineno">  489</span>&#160;      }</div>
<div class="line"><a name="l00490"></a><span class="lineno">  490</span>&#160;      <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00491"></a><span class="lineno">  491</span>&#160;    }</div>
<div class="line"><a name="l00492"></a><span class="lineno">  492</span>&#160;    <span class="comment">// If nothing else, try SACSegmentation</span></div>
<div class="line"><a name="l00493"></a><span class="lineno">  493</span>&#160;    <span class="keywordflow">default</span>:</div>
<div class="line"><a name="l00494"></a><span class="lineno">  494</span>&#160;    {</div>
<div class="line"><a name="l00495"></a><span class="lineno">  495</span>&#160;      <span class="keywordflow">return</span> (<a class="code" href="classpcl_1_1_s_a_c_segmentation.html">pcl::SACSegmentation&lt;PointT&gt;::initSACModel</a> (model_type));</div>
<div class="line"><a name="l00496"></a><span class="lineno">  496</span>&#160;    }</div>
<div class="line"><a name="l00497"></a><span class="lineno">  497</span>&#160;  }</div>
<div class="line"><a name="l00498"></a><span class="lineno">  498</span>&#160; </div>
<div class="line"><a name="l00499"></a><span class="lineno">  499</span>&#160;  <span class="keywordflow">return</span> (<span class="keyword">true</span>);</div>
<div class="line"><a name="l00500"></a><span class="lineno">  500</span>&#160;}</div>
<div class="ttc" id="aclasspcl_1_1_p_c_l_base_html_a09c70d8e06e3fb4f07903fe6f8d67869"><div class="ttname"><a href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">pcl::PCLBase::input_</a></div><div class="ttdeci">PointCloudConstPtr input_</div><div class="ttdoc">The input point cloud dataset.</div><div class="ttdef"><b>Definition:</b> pcl_base.h:150</div></div>
<div class="ttc" id="aclasspcl_1_1_p_c_l_base_html_aaee847c8a517ebf365bad2cb182a6626"><div class="ttname"><a href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">pcl::PCLBase::indices_</a></div><div class="ttdeci">IndicesPtr indices_</div><div class="ttdoc">A pointer to the vector of point indices to use.</div><div class="ttdef"><b>Definition:</b> pcl_base.h:153</div></div>
<div class="ttc" id="aclasspcl_1_1_s_a_c_segmentation_from_normals_html_a738ce9fb8455174564441597edcd0b9e"><div class="ttname"><a href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a738ce9fb8455174564441597edcd0b9e">pcl::SACSegmentationFromNormals::getClassName</a></div><div class="ttdeci">virtual std::string getClassName() const</div><div class="ttdoc">Class get name method.</div><div class="ttdef"><b>Definition:</b> sac_segmentation.h:425</div></div>
<div class="ttc" id="aclasspcl_1_1_s_a_c_segmentation_html"><div class="ttname"><a href="classpcl_1_1_s_a_c_segmentation.html">pcl::SACSegmentation</a></div><div class="ttdoc">SACSegmentation represents the Nodelet segmentation class for Sample Consensus methods and models,...</div><div class="ttdef"><b>Definition:</b> sac_segmentation.h:66</div></div>
<div class="ttc" id="aclasspcl_1_1_s_a_c_segmentation_html_a196b024d56223dd122e0a1c23773acab"><div class="ttname"><a href="classpcl_1_1_s_a_c_segmentation.html#a196b024d56223dd122e0a1c23773acab">pcl::SACSegmentation::model_</a></div><div class="ttdeci">SampleConsensusModelPtr model_</div><div class="ttdoc">The model that needs to be segmented.</div><div class="ttdef"><b>Definition:</b> sac_segmentation.h:260</div></div>
<div class="ttc" id="aclasspcl_1_1_s_a_c_segmentation_html_a7e4799ad1df36ce3b56a8c592a67bbf2"><div class="ttname"><a href="classpcl_1_1_s_a_c_segmentation.html#a7e4799ad1df36ce3b56a8c592a67bbf2">pcl::SACSegmentation::random_</a></div><div class="ttdeci">bool random_</div><div class="ttdoc">Set to true if we need a random seed.</div><div class="ttdef"><b>Definition:</b> sac_segmentation.h:299</div></div>
<div class="ttc" id="aclasspcl_1_1_s_a_c_segmentation_html_a873c817931f20ad93869526584c67e22"><div class="ttname"><a href="classpcl_1_1_s_a_c_segmentation.html#a873c817931f20ad93869526584c67e22">pcl::SACSegmentation::radius_min_</a></div><div class="ttdeci">double radius_min_</div><div class="ttdoc">The minimum and maximum radius limits for the model. Applicable to all models that estimate a radius.</div><div class="ttdef"><b>Definition:</b> sac_segmentation.h:278</div></div>
<div class="ttc" id="aclasspcl_1_1_s_a_c_segmentation_html_abc9924cedf7d0d013f860b8ad3054b69"><div class="ttname"><a href="classpcl_1_1_s_a_c_segmentation.html#abc9924cedf7d0d013f860b8ad3054b69">pcl::SACSegmentation::axis_</a></div><div class="ttdeci">Eigen::Vector3f axis_</div><div class="ttdoc">The axis along which we need to search for a model perpendicular to.</div><div class="ttdef"><b>Definition:</b> sac_segmentation.h:290</div></div>
<div class="ttc" id="aclasspcl_1_1_s_a_c_segmentation_html_ac40b9cd690894f581d507dabbeb89c3c"><div class="ttname"><a href="classpcl_1_1_s_a_c_segmentation.html#ac40b9cd690894f581d507dabbeb89c3c">pcl::SACSegmentation::eps_angle_</a></div><div class="ttdeci">double eps_angle_</div><div class="ttdoc">The maximum allowed difference between the model normal and the given axis.</div><div class="ttdef"><b>Definition:</b> sac_segmentation.h:287</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#aa6e65931b38d3cfa32afc34b60f896c8">&#9670;&nbsp;</a></span>setDistanceFromOrigin()</h2>

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<div class="memtemplate">
template&lt;typename PointT , typename PointNT &gt; </div>
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          <td class="memname">void <a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html">pcl::SACSegmentationFromNormals</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a>, PointNT &gt;::setDistanceFromOrigin </td>
          <td>(</td>
          <td class="paramtype">const double&#160;</td>
          <td class="paramname"><em>d</em></td><td>)</td>
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<p>Set the distance we expect a plane model to be from the origin </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">d</td><td>distance from the template plane modl to the origin </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00395"></a><span class="lineno">  395</span>&#160;{ <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a9757daa415a631f7d4ad088624f4491e">distance_from_origin_</a> = d; }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#a32a65052303a8ccc167c0182ab261df6">&#9670;&nbsp;</a></span>setInputNormals()</h2>

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<div class="memproto">
<div class="memtemplate">
template&lt;typename PointT , typename PointNT &gt; </div>
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          <td class="memname">void <a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html">pcl::SACSegmentationFromNormals</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a>, PointNT &gt;::setInputNormals </td>
          <td>(</td>
          <td class="paramtype">const PointCloudNConstPtr &amp;&#160;</td>
          <td class="paramname"><em>normals</em></td><td>)</td>
          <td></td>
        </tr>
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<p>Provide a pointer to the input dataset that contains the point normals of the XYZ dataset. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">normals</td><td>the const boost shared pointer to a <a class="el" href="classpcl_1_1_point_cloud.html" title="PointCloud represents the base class in PCL for storing collections of 3D points.">PointCloud</a> message </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160;{ <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a91b5f388af6d3b9c588f38fcb7a4e4be">normals_</a> = normals; }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#a902493eecbbfefce45767a98832d02c6">&#9670;&nbsp;</a></span>setMinMaxOpeningAngle()</h2>

<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;typename PointT , typename PointNT &gt; </div>
<table class="mlabels">
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      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html">pcl::SACSegmentationFromNormals</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a>, PointNT &gt;::setMinMaxOpeningAngle </td>
          <td>(</td>
          <td class="paramtype">const double &amp;&#160;</td>
          <td class="paramname"><em>min_angle</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const double &amp;&#160;</td>
          <td class="paramname"><em>max_angle</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
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<p>Set the minimum opning angle for a cone model. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramname">min_angle</td><td>the opening angle which we need minumum to validate a cone model. </td></tr>
    <tr><td class="paramname">max_angle</td><td>the opening angle which we need maximum to validate a cone model. </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00378"></a><span class="lineno">  378</span>&#160;      {</div>
<div class="line"><a name="l00379"></a><span class="lineno">  379</span>&#160;        <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a3cd9814bbc521a5f116a1f58cb3cc3d1">min_angle_</a> = min_angle;</div>
<div class="line"><a name="l00380"></a><span class="lineno">  380</span>&#160;        max_angle_ = max_angle;</div>
<div class="line"><a name="l00381"></a><span class="lineno">  381</span>&#160;      }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#adffe38382fbb0b511764faf9490140ca">&#9670;&nbsp;</a></span>setNormalDistanceWeight()</h2>

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<div class="memtemplate">
template&lt;typename PointT , typename PointNT &gt; </div>
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
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          <td class="memname">void <a class="el" href="classpcl_1_1_s_a_c_segmentation_from_normals.html">pcl::SACSegmentationFromNormals</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a>, PointNT &gt;::setNormalDistanceWeight </td>
          <td>(</td>
          <td class="paramtype">double&#160;</td>
          <td class="paramname"><em>distance_weight</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">inline</span></span>  </td>
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<p>Set the relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point normals and the plane normal. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">distance_weight</td><td>the distance/angular weight </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00365"></a><span class="lineno">  365</span>&#160;{ <a class="code" href="classpcl_1_1_s_a_c_segmentation_from_normals.html#a032a4b4f08619842f7f1c5602b22d9e4">distance_weight_</a> = distance_weight; }</div>
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<li>segmentation/include/pcl/segmentation/<a class="el" href="sac__segmentation_8h_source.html">sac_segmentation.h</a></li>
<li>segmentation/include/pcl/segmentation/impl/<a class="el" href="sac__segmentation_8hpp_source.html">sac_segmentation.hpp</a></li>
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